Search results for "Theoretical Computer Science"
showing 10 items of 1151 documents
Fuzzy Set Theory as a Methodological Bridge between Hard Sciences and Humanities
2013
In this paper, we will investigate the possible role of fuzzy set theory (FST), and more generally the ensemble of technologies and theoretical approaches known as soft computing, as a methodological bridge between hard sciences and humanities. We will try, building on previous works, to investigate the “family links” between these disciplines and show how FST may be of help in promoting a connection between the “two cultures”. We will discuss Carnap and his paradox of explication, the dilemma between imagination and rigor according to Bateson, the problem of interdisciplinarity, and the consequences of precision and exactness. C
An Efficient Algorithm for Helly Property Recognition in a Linear Hypergraph
2001
International audience; In this article we characterize bipartite graphs whose associated neighborhood hypergraphs have the Helly property. We examine incidence graphs both hypergraphs and linear hypergraphs and we give a polynomial algorithm to recognize if a linear hypergraph has the Helly property.
Hypergraph imaging: an overview
2002
Hypergraph theory as originally developed by Berge (Hypergraphe, Dunod, Paris, 1987) is a theory of finite combinatorial sets, modeling lot of problems of operational research and combinatorial optimization. This framework turns out to be very interesting for many other applications, in particular for computer vision. In this paper, we are going to survey the relationship between combinatorial sets and image processing. More precisely, we propose an overview of different applications from image hypergraph models to image analysis. It mainly focuses on the combinatorial representation of an image and shows the effectiveness of this approach to low level image processing; in particular to seg…
Interval Length Analysis in Multi Layer Model
2009
In this paper we present an hypothesis test of randomness based on the probability density function of the symmetrized Kulback-Leibler distance estimated, via a Monte Carlo simulation, by the distributions of the interval lengths detected using the Multi-Layer Model (MLM). The $MLM$ is based on the generation of several sub-samples of an input signal; in particular a set of optimal cut-set thresholds are applied to the data to detect signal properties. In this sense MLM is a general pattern detection method and it can be considered a preprocessing tool for pattern discovery. At the present the test has been evaluated on simulated signals which respect a particular tiled microarray approach …
Clustering with Terracotta
2008
Masteroppgave i informasjons- og kommunikasjonsteknologi 2008 – Universitetet i Agder, Grimstad In today’s java community, modern enterprise application products have more constraints and requirements then ever. High availability, application scalability and also good performance are required, which means an application is needed to be deployed on multiple JVMs, in other words, it has to be clustered or distributed. It is essential for the application to scale out well, has better performance and less complexity during development of clustering. This master thesis focuses on clustering with Terracotta which is a JVM level clustering technique. First I start analyzing the complexity when an …
Polysemy and gestaltist computation. some notes on gestaltist compositionality
2019
The paper is devoted to the concept of Gestaltist Compositionality. It is divided into two parts. The first part will introduce a minimal definition of «Gestaltist Compositionality». Moreover, it will prove that the computations implemented by this model of compositionality are sufficiently flexible to ensure the presence of several orders of semantic determination. The second part will be devoted to an investigation of the consequences of this result with particular reference to the identification of some versions of compositionality which relax the condition of semantic atomism without weakening the links of determination between understanding of the compounds and understanding of the com…
INDUCTIVE INFERENCE OF LIMITING PROGRAMS WITH BOUNDED NUMBER OF MIND CHANGES
1996
We consider inductive inference of total recursive functions in the case, when produced hypotheses are allowed some finite number of times to change “their mind” about each value of identifiable function. Such type of identification, which we call inductive inference of limiting programs with bounded number of mind changes, by its power lies somewhere between the traditional criteria of inductive inference and recently introduced inference of limiting programs. We consider such model of inductive inference for EX and BC types of identification, and we study • tradeoffs between the number of allowed mind changes and the number of anomalies, and • relations between classes of functions ident…
Dual types of hypotheses in inductive inference
2006
Several well-known inductive inference strategies change the actual hypothesis only when they discover that it “provably misclassifies” an example seen so far. This notion is made mathematically precise and its general power is characterized. In spite of its strength it is shown that this approach is not of “universal” power. Consequently, then hypotheses are considered which “unprovably misclassify” examples and the properties of this approach are studied. Among others it turns out that this type is of the same power as monotonic identification. Finally, it is shown that “universal” power can be achieved only when an unbounded number of alternations of these dual types of hypotheses is all…
Topological considerations in composing teams of learning machines
1995
Classes of total recursive functions may be identifiable by a team of strategies, but not by a single strategy, in accordance with a certain identification type (EX, FIN, etc.). Qualitative aspects in composing teams are considered. For each W ∉ EX all recursive strategies can be split into several families so that any team identifying W contains strategies from all the families. For W ∉ FIN the possibility of such splitting depends upon W. The relation between these phenomena and “voting” properties for types EX, FIN, etc. is revealed.
Model Identification of a Network as Compressing Sensing
2013
In many applications, it is important to derive information about the topology and the internal connections of dynamical systems interacting together. Examples can be found in fields as diverse as Economics, Neuroscience and Biochemistry. The paper deals with the problem of deriving a descriptive model of a network, collecting the node outputs as time series with no use of a priori insight on the topology, and unveiling an unknown structure as the estimate of a "sparse Wiener filter". A geometric interpretation of the problem in a pre-Hilbert space for wide-sense stochastic processes is provided. We cast the problem as the optimization of a cost function where a set of parameters are used t…